The present disclosure generally relates to the determination of mechanical quantities, and, more specifically, to methods utilizing one or more integrated computational elements for determining one or more mechanical quantities associated with a deformation force impacting a structure.
Issues with monitoring structural changes over time are becoming increasingly important due to the growing breadth of aging infrastructure throughout the United States and other countries. A number of breakdown factors, such as structural fatigue and like failure mechanisms, can impact a structure over time and may eventually make the structure unsuitable for its originally intended application. Such factors can include, but are not limited to, routine “wear and tear,” damage from chemical or environmental exposure, damage from applied loads or other displacement forces, internal stress, combinations thereof, and the like. As used herein, the term “structure” refers to any body having any shape and any function. In some instances, structural changes resulting from breakdown factors can be readily discerned with the naked eye. For example, surface cracking or large shape deformations may be readily observed with the naked eye. In other instances, however, structural changes may be much more subtle and difficult to discern, particularly those that occur internally within a structure.
In many instances, it can be desirable to quantify the degree of structural changes that have been experienced by a structure in order to determine if the structure has exceeded its working tolerances and structural failure is imminent. The degree of structural changes within a structure may often be measured by quantifying the conditions to which a structure has been exposed or is being exposed. Although a number of contact and non-contact sensors have been developed to monitor a wide range of environmental conditions including, but not limited to, temperature, pressure, moisture, and shock, these conditions may only provide limited value in quantifying structural breakdown. The direct measurement of displacement forces that are more directly associated with structural breakdown are often much more difficult to readily discern. Particularly in large structures, the sheer amount of structural surface area may represent a significant impediment to adequate structural characterization. Further, with many types of sensors, failure over the long term can present a significant concern.
In some instances, sensors may be incorporated within the body of a structure without significantly impacting the structure's intended function. In this regard, there has been some progress in incorporating nanomaterials within “smart” structures, in which the nanomaterials provide an internal sensing function. However, the incorporation of nanomaterials has not proven universally applicable to all types of structures or for measuring certain types of conditions impacting a structure. Moreover, nanomaterials can sometimes be expensive, and the sensing equipment for electrically or spectroscopically interrogating the nanomaterials may also be expensive and sensitive to field or process environments. Further, for spectral analyses, complicated deconvolution techniques can be required when interfering substances are present, particularly when analyzing a nanomaterial in low abundance.
With many types of sensors, feedback to an observer may not occur quickly enough for proactive control of a system or process to take place. For example, it may often be the case that a condition has already exceeded a threshold limit before it is even detected. Further, some types of sensors may require frequent calibration or inspection due to potential drift. Any of these factors can result in costly system or process downtime, either to respond to damage that has already occurred or to perform maintenance that prevents damage from occurring. Many applications could significantly benefit from robust sensors able to provide real-time or near real-time output of a wide range of conditions being monitored.